Avoiding Unnecessary Exposure of User Profile in Web Search
Keywords:
User History, Privacy, Websearch, User Profile, Web BrowserAbstract
While the amount of information on the web reliably develops, it offers come to be an expanding number of confused as to internet web indexes to find data that satisfy clients' specific individual needs. Modified hunt can be certain techniques to help seek through tweaking postings in the event that you have not at all like data desire. Decent customization criteria will rely on upon internet corpus and inexhaustible individual single profiles. Interestingly, for the reason that internet corpus is really resting for the server, re-positioning for the customer side is really transmission capacity engaged as it needs a colossal number associated with postings went to the customer sooner than re-positioning. Almost all individualized search products and functions on the web like bing, www and Google Customized Search put into act your second move toward to adjust effects for the server through analyzing collected confidential information, electron search histories and personalized interests. In this paper a technique named user preference hierarchy is proposed. Experimental results show that the proposed technique gives better results than existing technique such as personal web search.
References
Y. Zhu, L. Xiong, and C. Verdery, “Anonymizing User Profiles for Personalized Web Search,” Proc. 19th Int’l Conf. World Wide Web (WWW), pp.(1225-1226), 2010.
J. Castellı´-Roca, A. Viejo, and J. Herrera- Joancomartı´, “Preserving User’s Privacy in Web Search Engines,” Computer Comm.,vol.32, no. 13/14, pp. 1541-1551,2009.
Viejo and J.Castell a-Roca, “Using Social Networks to Distort Users’ Profiles Generated by Web Search”, Computer Networks, vol. 54, no. 9, pp. 1343-1357, 2010.
K.Ramanathan, J.Giraudi and A.Gupta, :Greating Hierararchcal User Profiles Using Wikipedia”, HP Labs, 2008.
J. Teevan, S.T. Dumais, and D.J. Liebling, “To Personalize or Notto Personalize: Modeling Queries with Variation in User Intent, “ Proc. 31st Ann. International ACM SIGIR Conf. Research and Development in Information Retrieval , pp 163-170, 2008.
Rajneesh Shrivastava, Shivlal Mewada and Pradeep Sharma, "An Approach to Give First Rank for Website and Webpage Through SEO", International Journal of Computer Sciences and Engineering, Volume-02, Issue-06, pp (13-17), Jun -2014,
G.Chen, H. Bai, L. Shou, and Y.Gao, “Ups: A Utility-Theoretic Approach to Privacy in Online Services,” J. Artificial Intelligence Research, vol. 39, pp. 633-662, 2010.
J>S.Breese, D.Heckerman, and C.M.Kadie, “Empirical Analysis of Predictive Algorithms for Collaborative Filtering”, Proceedings of 14th Conference Uncertainity in Artificial Intelligence (UAI), pp.43-52, 1998.
P.A. Chitra, W. Nejdl, R.Paiu and C. Kohlchutter, “Using ODP Metadat to Personalize Search”, Proceedings of 28th Ann. Int’l ACM SIGIR Conf. Research and Development Infromation retrieval, 2005.
A.Pretschner and S. gauch, “ontology-Based Personalized Search and Browsing,” Proc. IEEE 11th Int’l Conf. Tools with Artificial Intelligence (ICTAI’99), 1999.
Samanjeet Kaur and Sukhwinder Sharma,“Performing Efficient Phishing Web Page Detection”,International Journal of Computer Sciences and Engineering(IJCSE), pp 52-56, Vol.3, Issue 07, July 2015.
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